Order Fulfillment Mobile Robots Start to Deliver

A report from Interact Analysis found a huge potential growth opportunity in autonomous mobile robots (AMRs) for order fulfillment.

Kindred Sort Piece Picking Robot
Kindred

A report from Interact Analysis found a huge potential growth opportunity in autonomous mobile robots (AMRs) for order fulfillment.

The report discussed how the acquisition of Kiva Systems by Amazon has triggered two significant trends in the industry: the emergence of dozens of robotics start-ups and how the acquisition forced retailers and logistics companies to adopt automation to keep pace with Amazon. 

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The mobile robot market is predicted to transform over the next decade as autonomous platforms get adopted in warehouses. The rapid implementation is driven by an acute labor shortage and the e-commerce boom as customers demand for faster and cheaper delivery.

There has been a tipping point when implementing AMRs, the report argues. Excluding Amazon, more than 100,000 AMRs will have been deployed for order fulfillment by the end of 2020, with more than 580,000 robots expected to be installed over the next five years. 

Fig 1 Installed Base Year Forecast For Order Fulfillment Am Rs

Fewer than 300 sites have ordered fulfillment AMRs, however. Though, an "explosive growth" is predicted to a number of key drivers, such as the Amazon Effect. and low unemployment rates. 

Meanwhile, younger generations have begun to reject manual labor, creating a major shortage of warehouse workers, increasing demand for automated systems. The speed with which the technology has matured and moved beyond the early adopter stage has made deployment an increasingly attractive option. 

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“With Amazon deploying Kiva’s goods-to-person approach for order fulfilment, it’s easy to see why others like GreyOrange, Geek+ and Quicktron have followed in its footsteps, and arguably have seen greatest success so far," Ash Sharma, research director at Interact Analysis, says. “Despite this, AMR vendors have emerged with a variety of different approaches and sub-approaches. The question over which technology or approach will ‘win’ is not an easy one to answer. All approaches are forecast for strong growth (albeit at different paces and timeframes), and the approach preferred will depend on a number of variables.


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